Experimental validation of time optimal MPC on a linear drive system

Model Predictive Control (MPC) is a control technique capable of accounting for constraints on inputs, outputs and states, and traditionally makes a trade-off between output error and input cost. Originally developed for slow processes, MPC is nowadays also applied to faster systems such as mechatronic systems, thanks to increased computer power and more advanced algorithms. For these systems however, time optimality is often of the utmost importance, a feature that is not present in traditional MPC. This paper therefore presents and validates a new type of MPC, time optimal MPC (TOMPC), which minimizes the settling time. An experimental validation of TOMPC on a linear drive system with a sampling time of 5ms is performed and comparison with traditional MPC and linear feedback systems is given.

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